Computational design of an epitope-specific Keap1 binding antibody using hotspot residues grafting and CDR loop swapping
Open accessAbstract
Abstract Therapeutic and diagnostic applications of monoclonal antibodies often require careful selection of binders that recognize specific epitopes on the target molecule to exert a desired modulation of biological function. Here we present a proof-of-concept application for the rational design of an epitope-specific antibody binding with the target protein Keap1, by grafting pre-defined structural interaction patterns from the native binding partner protein, Nrf2, onto geometrically matched positions of a set of antibody scaffolds. The designed antibodies bind to Keap1 and block the Keap1-Nrf2 interaction in an epitope-specific way. One resulting antibody is further optimised to achieve low-nanomolar binding affinity by in silico redesign of the CDRH3 sequences. An X-ray co-crystal structure of one resulting design reveals that the actual binding orientation and interface with Keap1 is very close to the design model, despite an unexpected CDRH3 tilt and V H /V L interface deviation, which indicates that the modelling precision may be improved by taking into account simultaneous CDR loops conformation and V H /V L orientation optimisation upon antibody sequence change. Our study confirms that, given a pre-existing crystal structure of the target protein-protein interaction, hotspots grafting with CDR loop swapping is an attractive route to the rational design of an antibody targeting a pre-selected epitope.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Established structural bioinformatics methods such as homology modelling, protein-protein docking or protein interface prediction are already used for rational antibody design.
“Established structural bioinformatics methods such as homology modelling [6, 7], protein–protein docking [8, 9] or protein interface prediction [10] are already used for rational antibody design [11–13].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [11]
Liu and co-workers validated an approach in which binding site motifs from existing protein-protein complexes were transferred directly onto an antibody in a process termed 'hot-spot grafting'.
“In contrast, Liu and co-workers validated an approach in which binding site motifs from existing protein–protein complexes were transferred directly onto an antibody in a process termed ‘hot-spot grafting’ [11].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [11]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
<i>Coot</i> : model-building tools for molecular graphics
Emsley, P., & Cowtan, K. (2004) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444904019158 · Cited by 30,571 · see citing works
PROCHECK: a program to check the stereochemical quality of protein structures
Laskowski, R. A., MacArthur, M. W., Moss, D. S., & Thornton, J. M. (1993) · Journal of Applied Crystallography · doi:10.1107/s0021889892009944 · Cited by 24,581 · see citing works
<i>Phaser</i> crystallographic software
McCoy, A. J., Grosse-Kunstleve, R. W., Adams, P. D., Winn, M. D., Storoni, L. C., & Read, R. J. (2007) · Journal of Applied Crystallography · doi:10.1107/s0021889807021206 · Cited by 20,612 · see citing works
Refinement of Macromolecular Structures by the Maximum-Likelihood Method
Murshudov, G. N., Vagin, A. A., & Dodson, E. J. (1997) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444996012255 · Cited by 14,671 · see citing works
Overview of the <i>CCP</i> 4 suite and current developments
Winn, M. D., Ballard, C. C., Cowtan, K. D., Dodson, E. J., Emsley, P., Evans, P. R., Keegan, R. M., Krissinel, E. B., Leslie, A. G. W., McCoy, A., et al. (2011) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444910045749 · Cited by 12,353 · see citing works
Structure validation by Cα geometry: ϕ,ψ and Cβ deviation
Lovell, S. C., Davis, I. W., Arendall, W. B., de Bakker, P. I. W., Word, J. M., Prisant, M. G., Richardson, J. S., & Richardson, D. C. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10286 · Cited by 4,595 · see citing works
Somatic generation of antibody diversity
Tonegawa, S. (1983) · Nature · doi:10.1038/302575a0 · Cited by 4,005 · see citing works
Somatic generation of antibody diversity.
Matthyssens, G., Hozumi, N., & Tonegawa, S. (1976) · PubMed · Cited by 3,237 · see citing works
Rapid generation of functional human IgG antibodies derived from Fab-on-phage display libraries
Jostock, T., Vanhove, M., Brepoels, E., van Gool, R., Daukandt, M., Wehnert, A., van Hegelsom, R., Dransfield, D., Sexton, D., Devlin, M., et al. (2004) · Journal of Immunological Methods · doi:10.1016/j.jim.2004.03.014 · Cited by 2,562 · see citing works
Design of a Novel Globular Protein Fold with Atomic-Level Accuracy
Kuhlman, B. A., Dantas, G. A., Ireton, G. C., Varani, G., Stoddard, B. L., & Baker, D. A. (2003) · Science · doi:10.1126/science.1089427 · Cited by 1,666 · see citing works
Monoclonal antibodies: versatile platforms for cancer immunotherapy
Weiner, L. M., Surana, R., & Wang, S. (2010) · Nature reviews. Immunology · doi:10.1038/nri2744 · Cited by 1,282 · see citing works
Shape Complementarity at Protein/Protein Interfaces
Lawrence, M. C., & Colman, P. M. (1993) · Journal of Molecular Biology · doi:10.1006/jmbi.1993.1648 · Cited by 1,219 · see citing works
A graphical user interface to the CCP 4 program suite
Potterton, E. A., Briggs, P., Turkenburg, M., & Dodson, E. J. (2003) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444903008126 · Cited by 1,216 · see citing works
Shape complementarity at protein–protein interfaces
Norel, R., Lin, S. L., Wolfson, H. J., & Nussinov, R. (1994) · Biopolymers · doi:10.1002/bip.360340711 · Cited by 1,208 · see citing works
Potent antibody therapeutics by design
Carter, P. J. (2006) · Nature reviews. Immunology · doi:10.1038/nri1837 · Cited by 1,103 · see citing works
Macromolecular Modeling with Rosetta
Das, R., & Baker, D. A. (2008) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.77.062906.171838 · Cited by 995 · see citing works
Cullinan, S. B., Gordan, J. D., Jin, J., Harper, J. W., & Diehl, J. A. (2004) · Molecular and Cellular Biology · doi:10.1128/mcb.24.19.8477-8486.2004 · Cited by 986 · see citing works
Selecting and screening recombinant antibody libraries
Hoogenboom, H. R. (2005) · Nature Biotechnology · doi:10.1038/nbt1126 · Cited by 975 · see citing works
Vaguine, A. A., Richelle, J., & Wodak, S. J. (1999) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444998006684 · Cited by 887 · see citing works
Therapeutic antibodies for autoimmunity and inflammation
Chan, A. C., & Carter, P. J. (2010) · Nature reviews. Immunology · doi:10.1038/nri2761 · Cited by 840 · see citing works
Tong, K. I., Katoh, Y., Kusunoki, H., Itoh, K., Tanaka, T., & Yamamoto, M. (2006) · Molecular and Cellular Biology · doi:10.1128/mcb.26.8.2887-2900.2006 · Cited by 759 · cited 1× · see citing works
“Two hairpin loop motifs from Nrf2 (the stronger binding ETGE motif and the weaker binding DLG motif) have been reported to bind at the same region of two Keap1 Kelch domains 21 .”
Structural basis for defects of Keap1 activity provoked by its point mutations in lung cancer
Padmanabhan, B., Tong, K. I., Ohta, T., Nakamura, Y., Scharlock, M., Ohtsuji, M., Kang, M.-I., Kobayashi, A., Yokoyama, S., & Yamamoto, M. (2006) · Molecular Cell · doi:10.1016/j.molcel.2006.01.013 · Cited by 735 · see citing works
Standard conformations for the canonical structures of immunoglobulins 1 1Edited by I. A. Wilson
Al‐Lazikani, B., Lesk, A. M., & Chothia, C. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.1354 · Cited by 707 · see citing works
SAbDab: the structural antibody database
Dunbar, J., Krawczyk, K., Leem, J., Baker, T., Fuchs, A., Georges, G., Shi, J., & Deane, C. M. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1043 · Cited by 674 · see citing works
RosettaScripts: A Scripting Language Interface to the Rosetta Macromolecular Modeling Suite
Fleishman, S. J., Leaver‐Fay, A., Corn, J. E., Strauch, E., Khare, S. D., Koga, N., Ashworth, J. R., Murphy, P. M., Richter, F. M., Lemmon, G., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020161 · Cited by 659 · see citing works
Kozakov, D., Grove, L. E., Hall, D. R., Bohnuud, T., Mottarella, S. E., Luo, L., Xia, B., Beglov, D., & Vajda, S. (2015) · Nature Protocols · doi:10.1038/nprot.2015.043 · Cited by 643 · see citing works
Ma, B., Elkayam, T., Wolfson, H., & Nussinov, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1030237100 · Cited by 595 · see citing works
Computational Design of Proteins Targeting the Conserved Stem Region of Influenza Hemagglutinin
Fleishman, S. J., Whitehead, T. A., Ekiert, D. C., Dreyfus, C., Corn, J. E., Strauch, E.-M., Wilson, I. A., & Baker, D. (2011) · Science · doi:10.1126/science.1202617 · Cited by 585 · see citing works
Geometric hashing: an overview
Wolfson, H. J., & Rigoutsos, I. (1997) · IEEE Computational Science and Engineering · doi:10.1109/99.641604 · Cited by 562 · see citing works
Beyond natural antibodies: the power of in vitro display technologies
Bradbury, A. M., Sidhu, S. S., Dübel, S., & McCafferty, J. (2011) · Nature Biotechnology · doi:10.1038/nbt.1791 · Cited by 548 · see citing works
A new clustering of antibody CDR loop conformations
North, B., Lehmann, A., & Dunbrack, R. L. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.10.030 · Cited by 380 · see citing works
Whitehead, T. A., Chevalier, A. A., Song, Y., Dreyfus, C., Fleishman, S. J., de Mattos, C., Myers, C., Kamisetty, H., Blair, P. J., Wilson, I. A., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2214 · Cited by 364 · see citing works
Computational design of antibody-affinity improvement beyond in vivo maturation
Lippow, S. M., Wittrup, K. D., & Tidor, B. (2007) · Nature Biotechnology · doi:10.1038/nbt1336 · Cited by 342 · see citing works
Recombining germline-derived CDR sequences for creating diverse single-framework antibody libraries
Söderlind, E., Strandberg, L., Jirholt, P., Kobayashi, N., Alexeiva, V., Åberg, A.-M., Nilsson, A., Jansson, B., Ohlin, M., Wingren, C., et al. (2000) · Nature Biotechnology · doi:10.1038/78458 · Cited by 337 · see citing works
Morea, V., Tramontano, A. L., Rustici, M., Chothia, C., & Lesk, A. M. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.1442 · Cited by 327 · see citing works
Smith, C. A., & Kortemme, T. (2008) · Journal of Molecular Biology · doi:10.1016/j.jmb.2008.05.023 · Cited by 314 · see citing works
BiGGER: A new (soft) docking algorithm for predicting protein interactions
Palma, P. N., Krippahl, L., Wampler, J. E., & Moura, J. J. G. (2000) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(20000601)39:4 · Cited by 292 · see citing works
Protein–Protein Interaction Hotspots Carved into Sequences
Ofran, Y., & Rost, B. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030119 · Cited by 255 · see citing works
Analysis and improvements to Kabat and structurally correct numbering of antibody variable domains
Abhinandan, K. R., & Martin, A. C. R. (2008) · Molecular Immunology · doi:10.1016/j.molimm.2008.05.022 · Cited by 234 · see citing works
Stranges, P. B., & Kuhlman, B. A. (2012) · Protein Science · doi:10.1002/pro.2187 · Cited by 233 · see citing works
Structural classification of CDR‐H3 in antibodies
Shirai, H., Kidera, A., & Nakamura, H. (1996) · FEBS Letters · doi:10.1016/s0014-5793(96)01252-5 · Cited by 223 · see citing works
Computer-aided antibody design
Kuroda, D., Shirai, H., Jacobson, M. P., & Nakamura, H. (2012) · Protein Engineering Design and Selection · doi:10.1093/protein/gzs024 · Cited by 223 · see citing works
Methodological advances: the unsung heroes of the GPCR structural revolution
Ghosh, E., Kumari, P., Jaiman, D., & Shukla, A. K. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3933 · Cited by 201 · see citing works
Sivasubramanian, A., Sircar, A., Chaudhury, S., & Gray, J. J. (2008) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22309 · Cited by 185 · see citing works
Structural basis of agrin–LRP4–MuSK signalingPreprint
Zong, Y., Zhang, B., Gu, S., Lee, K., Zhou, J., Yao, G., Figueiredo, D., Perry, K., Mei, L., & Jin, R. (2012) · Genes & Development · doi:10.1101/gad.180885.111 · Cited by 184 · see citing works
Structures of protective antibodies reveal sites of vulnerability on Ebola virus
Murin, C. D., Fusco, M. L., Bornholdt, Z. A., Qiu, X., Olinger, G. G., Zeitlin, L., Kobinger, G. P., Ward, A. B., & Saphire, E. O. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1414164111 · Cited by 183 · see citing works
Wnt Antagonists Bind through a Short Peptide to the First β-Propeller Domain of LRP5/6
Bourhis, E., Wang, W., Tam, C., Hwang, J., Zhang, Y., Spittler, D., Huang, O. W., Gong, Y., Estevez, A., Zilberleyb, I., et al. (2011) · Structure · doi:10.1016/j.str.2011.07.005 · Cited by 169 · see citing works
Sircar, A., & Gray, J. J. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000644 · Cited by 166 · see citing works
A De Novo Protein Binding Pair By Computational Design and Directed Evolution
Karanicolas, J., Corn, J. E., Chen, I., Joachimiak, Ł. A., Dym, O., Peck, S. H., Albeck, S., Unger, T., Hu, W., Liu, G., et al. (2011) · Molecular Cell · doi:10.1016/j.molcel.2011.03.010 · Cited by 164 · see citing works
Zdanov, A. S., Li, Y., Bundle, D. R., Deng, S. J., MacKenzie, C. R., Narang, S. A., Young, N. M., & Cygler, M. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.14.6423 · Cited by 153 · see citing works
Tools to therapeutically harness the human antibody response
Wilson, P. C., & Andrews, S. F. (2012) · Nature reviews. Immunology · doi:10.1038/nri3285 · Cited by 146 · see citing works
Rational design of antibodies targeting specific epitopes within intrinsically disordered proteins
Sormanni, P., Aprile, F. A., & Vendruscolo, M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1422401112 · Cited by 145 · see citing works
Structure-Guided Design of an Anti-dengue Antibody Directed to a Non-immunodominant Epitope
Robinson, L. N., Tharakaraman, K., Rowley, K. J., Costa, V. V., Chan, K. R., Wong, Y. H., Ong, L. C., Tan, H. C., Koch, T., Cain, D., et al. (2015) · Cell · doi:10.1016/j.cell.2015.06.057 · Cited by 140 · see citing works
ABangle: characterising the VH-VL orientation in antibodies
Dunbar, J., Fuchs, A., Shi, J., & Deane, C. M. (2013) · Protein Engineering Design and Selection · doi:10.1093/protein/gzt020 · Cited by 125 · see citing works
Lapidoth, G. D., Baran, D., Pszolla, G. M., Norn, C., Alon, A., Tyka, M. D., & Fleishman, S. J. (2015) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24779 · Cited by 107 · see citing works
Role of the Biomolecular Energy Gap in Protein Design, Structure, and Evolution
Fleishman, S. J., & Baker, D. A. (2012) · Cell · doi:10.1016/j.cell.2012.03.016 · Cited by 104 · see citing works
Prediction of loop geometries using a generalized born model of solvation effects
Rapp, C. S., & Friesner, R. A. (1999) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19990501)35:2 · Cited by 103 · see citing works
Cain, K., Peters, S. J., Hailu, H., Sweeney, B., Stephens, P. E., Heads, J. T., Sarkar, K., Ventom, A., Page, C., & Dickson, A. J. (2013) · Biotechnology Progress · doi:10.1002/btpr.1693 · Cited by 96 · see citing works
Nonnatural protein–protein interaction-pair design by key residues grafting
Liu, S., Liu, S., Zhu, X., Liang, H., Cao, A., Chang, Z., & Lai, L. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0606198104 · Cited by 80 · see citing works
Antibody-enabled small-molecule drug discovery
Lawson, A. D. G. (2012) · Nature Reviews Drug Discovery · doi:10.1038/nrd3756 · Cited by 80 · see citing works
Li, T., Pantazes, R. J., & Maranas, C. D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0105954 · Cited by 79 · see citing works
Antibody fragments as tools in crystallography
Griffin, L., & Lawson, A. D. G. (2011) · Clinical & Experimental Immunology · doi:10.1111/j.1365-2249.2011.04427.x · Cited by 76 · see citing works
Tharakaraman, K., Robinson, L. N., Hatas, A., Chen, Y., Siyue, L., Raguram, S., Sasisekharan, V., Wogan, G. N., & Sasisekharan, R. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1303645110 · Cited by 65 · see citing works
Computational design of protein–protein interactions
Schreiber, G., & Fleishman, S. J. (2013) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2013.08.003 · Cited by 63 · see citing works
Hotspot-Centric De Novo Design of Protein Binders
Fleishman, S. J., Corn, J. E., Strauch, E., Whitehead, T. A., Karanicolas, J., & Baker, D. A. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2011.09.001 · Cited by 50 · see citing works
Protein Engineering by Combined Computational and In Vitro Evolution Approaches
Rosenfeld, L., Heyne, M., Shifman, J. M., & Papo, N. (2016) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2016.03.002 · Cited by 41 · see citing works
Jordan, J. L., Arndt, J. W., Hanf, K. J. M., Li, G., Hall, J., Demarest, S. J., Huang, F., Wu, X., Miller, B., Glaser, S., et al. (2009) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22502 · Cited by 39 · see citing works
Transcriptionally Active Polymerase Chain Reaction (TAP)
Liang, X., Teng, A., Braun, D. M., Felgner, J. H., Wang, Y., Baker, S. I., Chen, S., Zelphati, O., & Felgner, P. L. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m110652200 · Cited by 36 · see citing works
Prediction of hypervariable CDR-H3 loop structures in antibodies
Reczko, M., Martin, A. C. R., Bohr, H. G., & Suhai, S. (1995) · Protein Engineering Design and Selection · doi:10.1093/protein/8.4.389 · Cited by 34 · see citing works
Tan, Y. S., Spring, D. R., Abell, C., & Verma, C. S. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/ct5010577 · Cited by 32 · see citing works
Shining light on a new class of hydrogels
Jay, S. M., & Saltzman, W. M. (2009) · Nature Biotechnology · doi:10.1038/nbt0609-543 · Cited by 29 · see citing works
An antibody loop replacement design feasibility study and a loop-swapped dimer structure
Clark, L. A., Boriack‐Sjodin, P. A., Day, E. S., Eldredge, J. K., Fitch, C., Jarpe, M. B., Miller, S., Li, Y., Simon, K. J., & van Vlijmen, H. (2008) · Protein Engineering Design and Selection · doi:10.1093/protein/gzn072 · Cited by 14 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Computational approaches to therapeutic antibody design: established methods and emerging trends
Norman, R. A., Ambrosetti, F., Bonvin, A. M. J. J., Colwell, L. J., Kelm, S., Kumar, S., & Krawczyk, K. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbz095 · Cited by 219 · see citing works
“In contrast, Liu and coworkers validated an approach in which binding site motifs from existing protein–protein complexes were transferred directly onto an antibody in a process termed ‘hot-spot grafting’ [11].”
BackgroundThird generation antibody discovery methods: in silico rational design
Sormanni, P., Aprile, F. A., & Vendruscolo, M. (2018) · Chemical Society Reviews · doi:10.1039/c8cs00523k · Cited by 136 · see citing works
Advances in computational structure-based antibody design
Hummer, A. M., Abanades, B., & Deane, C. M. (2022) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2022.102379 · Cited by 105 · see citing works
Computational design of epitope-specific functional antibodies
Nimrod, G., Fischman, S., Austin, M., Herman, A., Keyes, F., Leiderman, O., Hargreaves, D., Strajbl, M., Breed, J., Klompus, S., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.10.081 · Cited by 77 · see citing works
Assessing human B cell repertoire diversity and convergence
Imkeller, K., & Wardemann, H. (2018) · Immunological Reviews · doi:10.1111/imr.12670 · Cited by 61 · see citing works
Structural and mechanistic insights into the Keap1-Nrf2 system as a route to drug discovery
Madden, S. K., & Itzhaki, L. S. (2020) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2020.140405 · Cited by 60 · see citing works
Computational design of antibodies
Fischman, S., & Ofran, Y. (2018) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2018.04.007 · Cited by 56 · see citing works
Homology Modeling-Based in Silico Affinity Maturation Improves the Affinity of a Nanobody
Cheng, X. M., Wang, J., Kang, G., Hu, M., Yuan, B., Zhang, Y., & Huang, H. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20174187 · Cited by 55 · see citing works
How can we discover developable antibody-based biotherapeutics?
Bauer, J., Rajagopal, N., Gupta, P., Gupta, P. K., Nixon, A. E., & Kumar, S. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1221626 · Cited by 27 · see citing works
Deep phylogeny of cancer drivers and compensatory mutations
Rochman, N. D., Wolf, Y. I., & Koonin, E. V. (2020) · Communications Biology · doi:10.1038/s42003-020-01276-7 · Cited by 24 · see citing works
Adaption of human antibody λ and κ light chain architectures to CDR repertoires
van der Kant, R., Bauer, J., Karow‐Zwick, A. R., Kube, S., Garidel, P., Blech, M., Rousseau, F., & Schymkowitz, J. W. H. (2019) · Protein Engineering Design and Selection · doi:10.1093/protein/gzz012 · Cited by 21 · see citing works
Madden, S. K., Perez‐Riba, A., & Itzhaki, L. S. (2019) · Protein Science · doi:10.1002/pro.3586 · Cited by 17 · see citing works
High-Throughput Antibody Structure Modeling and Design Using ABodyBuilder
Leem, J., & Deane, C. M. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-8736-8_21 · Cited by 15 · see citing works
Structure-Guided Design of a Peptide Lock for Modular Peptide Binders
Ernst, P. J., Zosel, F., Reichen, C., Nettels, D., Schuler, B., & Plückthun, A. (2020) · ACS Chemical Biology · doi:10.1021/acschembio.9b00928 · Cited by 14 · see citing works
Gallo, E. (2024) · Molecular Biotechnology · doi:10.1007/s12033-024-01064-2 · Cited by 16 · see citing works
Understanding and Modulating Antibody Fine Specificity: Lessons from Combinatorial Biology
Rojas, G. (2022) · Antibodies · doi:10.3390/antib11030048 · Cited by 11 · see citing works
Gopal, R., Fitzpatrick, E. G., Pentakota, N., Jayaraman, A., Tharakaraman, K., & Capila, I. (2022) · Viruses · doi:10.3390/v14122694 · Cited by 12 · see citing works
Analysis of conformational stability of interacting residues in protein binding interfaces
Chauhan, V. M., & Pantazes, R. J. (2022) · Protein Engineering Design and Selection · doi:10.1093/protein/gzad016 · Cited by 10 · see citing works
Creation of artificial protein–protein interactions using α-helices as interfaces
Yagi, S., Akanuma, S., & Yamagishi, A. (2017) · Biophysical Reviews · doi:10.1007/s12551-017-0352-9 · Cited by 9 · see citing works
Prediction of Paratope–Epitope Pairs Using Convolutional Neural Networks
Li, D., Pucci, F., & Rooman, M. J. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25105434 · Cited by 10 · see citing works
MutDock: A computational docking approach for fixed-backbone protein scaffold design
Chauhan, V. M., & Pantazes, R. J. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.933400 · Cited by 8 · see citing works
AntiBMPNN: Structure‐Guided Graph Neural Networks for Precision Antibody Engineering
Sun, Z., Yuan, J., Jaiswal, D., Ge, J., Liang, T., Wei, J., Cao, J., Li, Y., Chu, X., Chen, Y., et al. (2025) · Advanced Science · doi:10.1002/advs.202504278 · Cited by 7 · see citing works
Rosetta-Enabled Structural Prediction of Permissive Loop Insertion Sites in Proteins
Plaks, J. G., Brewer, J. A., Jacobsen, N. K., McKenna, M., Uzarski, J. R., Lawton, T. J., Filocamo, S. F., & Kaar, J. L. (2020) · Biochemistry · doi:10.1021/acs.biochem.0c00533 · Cited by 6 · see citing works
Progress toward new function and design of extracellular G protein-coupled receptor nanobodies
Schlimgen, R. R., & Volkman, B. F. (2025) · Molecular Pharmacology · doi:10.1016/j.molpha.2025.100054 · Cited by 5 · see citing works
Richard, A. C., & Pantazes, R. J. (2024) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.26773 · Cited by 6 · see citing works
Kadir, F. F. N. A., Nordin, M. A. C., Shuid, A. N., & Omar, M. T. C. (2024) · Molecular Simulation · doi:10.1080/08927022.2024.2378833 · Cited by 4 · see citing works
Higher Affinity Antibodies Bind With Lower Hydration and Flexibility in Large Scale Simulations
Wong, M. T. Y., Kelm, S., Liu, X., Taylor, R. D., BAKER, T. S., & Essex, J. W. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.884110 · Cited by 4 · see citing works
Fischman, S., Levin, I., Rondeau, J., Štrajbl, M., Lehmann, S., Huber, T., Nimrod, G., Cèbe, R., Omer, D., Kovařík, J., et al. (2023) · Communications Biology · doi:10.1038/s42003-023-05369-x · Cited by 4 · see citing works
Yadav, A. J., Bhagat, K., Sharma, A., & Padhi, A. K. (2025) · Advances in protein chemistry and structural biology · doi:10.1016/bs.apcsb.2024.10.011 · Cited by 3 · see citing works
Mimic antibodies: leveraging ligand mimicry for epitope-targeted antibody discovery
Abanades, B., López-Morales, J., Tanasijević, I., Wagner, C., Speck, J., Fenn, S., Kettenberger, H., Butzer, J., Mundigl, S., Martinkus, K., et al. (2026) · mAbs · doi:10.1080/19420862.2026.2719289 · Cited by 2 · see citing works
Modified heated dynamics and deep mutational scanning enhance anti-CXCR2 antibody affinity
Omar, M. T. C., Choong, Y. S., & Omar, M. T. C. (2025) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2025.2584341 · Cited by 1 · see citing works
Sachdev, S., & Cheloha, R. W. (2026) · British Journal of Pharmacology · doi:10.1111/bph.70519 · Cited by 1 · see citing works
Zhang, Y., Liu, H., Bao, Y., & Peng, Z. (2024) · Fishes · doi:10.3390/fishes9100409 · Cited by 1 · see citing works
Exploring the binding of rationally engineered tandem-repeat proteins to E3 ubiquitin ligase Keap1
Madden, S. K., & Itzhaki, L. S. (2021) · Protein Engineering Design and Selection · doi:10.1093/protein/gzab027 · Cited by 1 · see citing works
Antibody Modeling, Engineering, and Design
Fischman, S., & Ofran, Y. (2018) · Springer eBooks · doi:10.1007/978-3-642-35943-9_10083-1
Bauer, J., Kube, S., Gupta, P. K., & Kumar, S. (2024) · Springer eBooks · doi:10.1007/978-3-031-62007-2_14
CDRxAbs: antibody small-molecule conjugates with computationally designed target-binding synergy
Wang, J., Aceves, A. J., Friesenhahn, N. J., & Mayo, S. L. (2025) · Protein Engineering Design and Selection · doi:10.1093/protein/gzaf004
MIMOSA: Guiding De Novo Antibody Design with Natural Interaction FingerprintsPreprint
Abanades, B., Roncoli, A., Bhagawati, M., Kessel, P., Imhof-Jung, S., Doerr, D., Schilz, J., Vasilaki, S., Seeger, F., Bonvin, A. M. J. J., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.09.24.753155
- Authors
- Liu, X., Taylor, R. D., Griffin, L., Coker, S.-F., Adams, R., Ceska, T., Shi, J., Lawson, A. D. G., & Baker, T.
- Affiliations
- UCB Pharma (United Kingdom) (GB)
- UCB Pharma (Belgium) (BE)
- Corresponding author
- Liu, Xiaofeng
- Baker, Terry
- ORCID
- Venue
- Scientific Reports
- Published
- 2017-01-27
- Volume
- 7
- Issue
- 1
- Pages
- 41306-41306
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC5269676
- OpenAlex
- W2582870217
- Cited by
- 39
- References
- 72
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 6 · 2023: 2 · 2022: 6 · 2021: 1 · 2020: 4 · 2019: 4 · 2018: 6 · 2017: 1
- FWCI
- 3.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Keywords
- Keap1, Nrf2, Keap1-Nrf2 interaction, hot spot residues, antibody scaffolds, protein-protein interaction inhibition, co-crystal structure, rational antibody design
- MeSH terms
- Kelch-Like ECH-Associated Protein 1, Amino Acid Sequence, Antibodies, Monoclonal, Antibody Affinity, Epitopes, Computer Simulation, Humans, Protein Binding, Crystallography, X-Ray, Complementarity Determining Regions, NF-E2-Related Factor 2
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
